Evidence map›Paper›PMID 32272927›Full record

ArticleBMC medicine2020

Characteristics, service use and mortality of clusters of multimorbid patients in England: a population-based study.

Yajing Zhu, Duncan Edwards, Jonathan Mant, Rupert A Payne, Steven Kiddle

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In one paragraph

Article in BMC medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yajing ZhuMRC Biostatistics Unit, University of Cambridge, Cambridge, CB2 0SR, UK. yajing.zhu@mrc-bsu.cam.ac.uk.
Duncan EdwardsDepartment of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Worts' Causeway, Cambridge, CB1 8RN, UK.
Jonathan MantDepartment of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Worts' Causeway, Cambridge, CB1 8RN, UK.
Rupert A PayneCentre for Academic Primary Care, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2PS, UK.
Steven KiddleMRC Biostatistics Unit, University of Cambridge, Cambridge, CB2 0SR, UK.

Funding

Medical Research Council MC_UU_00002/10Medical Research Council MR/P021573/1
6 · The paper itself

Abstract

backgroundMultimorbidity is associated with mortality and service use, with specific types of multimorbidity having differential effects. Additionally, multimorbidity is often negatively associated with participation in research cohorts. Therefore, we set out to identify clusters of multimorbidity patients and how they are differentially associated with mortality and service use across age groups in a population-representative sample.

methodsLinked primary and secondary care electronic health records contributed by 382 general practices in England to the Clinical Practice Research Datalink (CPRD) were used. The study included a representative set of multimorbid adults (18 years old or more, N = 113,211) with two or more long-term conditions (a total of 38 conditions were included). A random set of 80% of the multimorbid patients (N = 90,571) were stratified by age groups and clustered using latent class analysis. Consistency between obtained multimorbidity phenotypes, classification quality and associations with demographic characteristics and primary outcomes (GP consultations, hospitalisations, regular medications and mortality) was validated in the remaining 20% of multimorbid patients (N = 22,640).

resultsWe identified 20 patient clusters across four age strata. The clusters with the highest mortality comprised psychoactive substance and alcohol misuse (aged 18-64); coronary heart disease, depression and pain (aged 65-84); and coronary heart disease, heart failure and atrial fibrillation (aged 85+). The clusters with the highest service use coincided with those with the highest mortality for people aged over 65. For people aged 18-64, the cluster with the highest service use comprised depression, anxiety and pain. The majority of 85+-year-old multimorbid patients belonged to the cluster with the lowest service use and mortality for that age range. Pain featured in 13 clusters.

conclusionsThis work has highlighted patterns of multimorbidity that have implications for health services. These include the importance of psychoactive substance and alcohol misuse in people under the age of 65, of co-morbid depression and coronary heart disease in people aged 65-84 and of cardiovascular disease in people aged 85+.

Indexed as

MultimorbidityAdolescentAdultAgedAged, 80 and overEnglandFemaleHumansMaleMiddle AgedYoung AdultAge stratificationChronic conditionsLatent class analysisMultimorbidity phenotypePattern recognitionValidation

Identifiers

PMID32272927
PMCPMC7147068

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.